Visual Odometry

Summary

Visual odometry recovers the relative motion of a camera based on motion
flow. Features are typically tracked between frames and a robust estimation
algorithm applied to deal with outliers. Our approach further addresses the
problem of degenerate data, which commonly occurs due to low
textured surfaces, bad lighting conditions with bright areas and shadows, as
well as motion blur.

Publications

I gave a live demo of my visual odometry work to the DARPA LAGR program manager in
San Antonio, Texas, in January 2008.

Example sequence

A short sequence of features as tracked by our visual odometry on data acquired
at NIST (click on the image for movie - 5MB):

It is well known that standard RANSAC approaches fail
when applied to degenerate data. For visual odometry, the three-point algorithm is
commonly used, but produces inconsistent results (see figures below). Our
approach in contrast provides consistent results.